Using This Report

Using this Report

This report was designed to visualize genetic patterns surrounding functional health pathways and biological processes. Here at GeneSavvy™ we strongly believe that genetic susceptibilities are created by compounded genetic and environmental influences. The goal is to identify genetic patterns that show us functional health and biological processes that might not be able to handle the current toxic environmental loads. If we find patterns that suggest possible pathway or process disruption, we can adjust our environment to support the disruptions, reduce environmental burdens, and move towards more vibrant health!

Suggested first steps for quick clinical actions:

  • Step One:

    Review High Priority gene networks and utilize clinical tools to explore these networks as a differential diagnosis or potential underlying cause of current diagnosis that could be used for more personalized treatment protocols.

  • Step Two:

    Review Rare and High Impact gene variants that are most likely to cause gene dysfunction.

    • Prioritize genes that are involved in multiple networks (Network Count) as they could be the root of disruption for many related pathways and processes that share similar symptoms.
    • Variants with “OMIM Var” associations have been referenced as disease associated.
    • Remember to focus on the functional role of the GENE more than the specific variant. Variants increase or decrease gene activity so consider the downstream effects that might happen if that genes activity is altered due to these variants.

  • Step Three:

    Review Medium Priority gene networks with highest relation to clinical presentation. Use these networks to further help identify genetic or environmental patterns that can be explored as a differential diagnosis or potential underlying cause of current diagnosis that could be used for more personalized treatment protocols.

Key Descriptions:

Gene Networks:

Our GeneSavvy gene networks are built using a Boolean model to find genes related to the functional health terms used in your report. After collecting the relational genes, we use a practical scoring, function-based algorithm, to calculate relevance and extract the top relevant genes for your report. We take all these factors to create a network score that we translate into priority predictions.

The Colors:

We use colors to help you scan quickly for patterns within this report.

Genes symbols in:

GREY  means there were no exome variants found in that gene.

BLUE  means there were COMMON SNP variants found. These are variants that are found in greater than 25% of the population, many of these variants have been referenced in research papers and associated to different phenotypes and traits.

GREEN  means there were variants found with only LOW predicted impact.

YELLOW  means there were variants found with MODERATE predicted impact.

ORANGE  means there were RARE & UNCOMMON variants found with MODERATE predicted impact.

RED  means there were variants found with HIGH predicted impact.

PURPLE  means there were variants found that our GeneSavvy algorithms flagged as one of the TOP 25% HIGHEST IMPACT VARIANTS out of all your genes. Genes listed in PURPLE should be the first genes to research as potentially causative to the health concern.

Low Predicted Impact:

Low predicted impact variants are usually synonymous variants that don’t cause any amino acid changes or variants in areas that don’t usually lead to impact on gene efficiency

Moderate Predicted Impact:

Moderate predicted impact variants are usually nonsynonymous variants that do change the amino acid. This category of impact also contains insertions or deletions in multiples of 3 that don’t cause a disruptive frameshift.

High Predicted Impact:

 High predicted impact variants are usually start or stop loss variants as well as disruptive frameshifts, major deletions, insertions or variants in splice site donors and splice site acceptors regions. These variants have high potential to impact gene functionality and efficiency.


Rare genetic variants are usually given higher predicted impact compared to common variants. If the variant is found in 99% of our population then it has less chance to be a variant that directly leads to a health condition.

  • Very Rare: Less than .01% of Population
  • Rare: Less than 1% of Population
  • Uncommon: Less than 5% of Population
  • Common: Greater than 5% of Population
  • Unknown: No Population Frequency Data

Potentially Significant Variants:

Interesting rare variants with high predicted impact on gene activity. These variants should be first to research.

Common SNPs:

Technically SNPs (Single Nucleotide Polymorphisms) are only classified as SNPs as they become commonly found in the population. These tend to have less impact on specific health conditions but they can still be key to finding patterns. Common SNPs are shown as BLUE in our reports.


How many times we confirmed that variant to be true during the sequencing process.
High depth = more confidence that these rare and sometimes never before seen variants are real.

Clickable Links:

Several areas in our report contain clickable links to quickly move to sections within the report or external sites for further research.

  • Gene Network Names: Click on the network names to quickly move to the network descriptions within the report.
  • Gene Symbols: The gene symbols within the report redirect to their data page on which contains tons of great information for further research including genefunctions, pathways, associated diseases, and treatments.
  • rsID Numbers: The rsID numbers within the report redirect to their associated data on the NCBI website at which can provide great research information specific to the SNP referenced.
  • OMIM Numbers: The OMIM numbers within the report redirect to their associated data on the OMIM website at “OMIM Gene” numbers will redirect to the gene information on OMIM while “OMIMVar” numbers will redirect to the specific variant content that is referenced. OMIM contains great information for further research, specifically for Gene/Variant associations in clinical applications.
**More specific data for all variants used to build this report can be reviewed in the text data file provided by GeneSavvy. If you did not receive your data file, please contact us so we can provide the associated reference file for you.**

Still have questions? Contact us at [email protected] so we can help!